In nuclear medicine (NM) imaging, such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) imaging, radiopharmaceuticals (RP) are administered internally to a patient. Detectors (e.g., gamma cameras), typically installed on a gantry, capture the radiation emitted by the radiopharmaceuticals and this information is used, by a computer, to form images. The NM images primarily show physiological function of, for example, the patient or a portion of the patient being imaged.
However, significant efforts have been invested to develop automated medical diagnostic methods. In NM imaging, the image data are usually subjected to significant noise or uncertainty. A key problem is the uncertainty in a specific patient scan cannot be estimated just from the image results of a single scan. In NM image noise (or reconstruction artifacts such as blobs) can appear similarly to real findings, and even sophisticated filters cannot resolve the noise. For example, measuring standard deviation within a homogenous region on the images, or even on the acquired projections, is not a good indication for the true uncertainty in the data which is usually significantly higher.